“The acquisition extends Bigtincan’s lead in AI-driven revenue intelligence by improving B2B sales organization’s ability to scale by delivering insights and recommendations directly to sales reps for better decision-making to increase revenue,” the firm told investors. “The SalesDirector.ai technology links people, activity, and engagement across the buyer’s journey to derive insights, including opportunity risk and relationship strength, and then makes intelligent recommendations. By capturing all sales, marketing, and customer success activity the technology drives actionable revenue insights required to make the right business decisions.”
Bigtincan stated that SalesDirector’s technology would improve its AI-powered insights capabilities and forecasting accuracy.
SalesDirector ingests data from GSuite/Gmail, Slack, Microsoft Office, and Microsoft Exchange and feeds contact data (e.g., Title, Department, Level, Phone) to Salesforce and Microsoft Dynamics. SalesDirector also captures Engagement Signals and writes them back to CRMs as custom fields:
Executive Engaged on Opportunity / Account
Single or Multi-Threaded Opportunity Relationship
Last QBR Complete / Next QBR Scheduled
Partner / Sales Engineer Engaged on Opportunity
Next Step / Meeting Scheduled
AI tools include stakeholder identification, individuals who are supporters or detractors, disengaged stakeholders, account risk scoring, sentiment analysis, and deal health.
SalesDirector.AI Account Insights and Next Best Actions.
“Every organization has to be more productive,” said Bigtincan CEO David Keane. “With the Sales Enablement market shifting towards a more holistic approach encompassing Revenue Enablement, we can deliver more value to our customers by providing full-cycle sellers with AI-driven recommendations on the next best actions based on intelligent sales analytics from SalesDirector.ai.”
SalesDirector pricing begins at $29 per user per month for activity capture. Revenue Insights pricing is not published.
AI-assisted stakeholder mapping.
Bigtincan will incorporate SalesDirector’s functionality into its product suite and phase out the SalesDirector brand.
“Traditionally, when we do small tech-focused acquisitions, they become part of the Bigtincan product suite, so that capability gets added to the existing platform we have,” said Keane. “We don’t tend to run these things as separate businesses, mostly because we miss out on some of the benefits for our shareholders of taking it all together and taking that technology and really getting in the platform. This is no different than our existing strategy – embed, connect it all together and make it something that our customers can choose to add. We do believe that it is all about choice, and we want people to be able to buy these technologies from us as additional value-added options. I think that’s going to be the case here as well.”
Bigtincan paid $1.2 million in cash and equity for SalesDirector.
The entire SalesDirector team is joining Bigtincan.
Bigtincan, listed on the Australian Stock Exchange, has acquired a series of RevTech companies, including ClearSlide, Brainshark, and VoiceVibes.
Happy New Year. While off on vacation last week, I published an interview with Salesloft SVP of Product Management Frank Dale concerning Ethical AI. He joined Salesloft in November 2019 when Costello, the opportunity management firm he founded, was acquired by Salesloft. He has served as either CEO or COO at several investor-backed software companies, including Compendium, which Oracle acquired.
Dale earned a BA and MA from Valparaiso University with a concentration in ethics. He also received an MBA from the Kelley School of Business at Indiana University.
What experience have you had developing AI tools?
As the SVP of Product Management at Salesloft, I am working with our team to bring Rhythm, Salesloft’s AI-powered signal-to-action engine platform, to life. Rhythm ingests every signal from the Salesloft platform as well as signals from partner solutions via APIs, ranks and prioritizes those signals, and then produces a prioritized list of actions. The action list gives sellers a clear, prioritized list of actions that will be the most impactful each day, along with an expected outcome prediction. In addition to simplifying a seller’s day-to-day, it helps them build their skills by providing the context about why each action matters.
AI is becoming increasingly important in RevTech, with many of our interactions being mediated by AI. Where do you see AI having the biggest impact on Sales reps between now and 2025?
AI will enable significant improvements in both seller efficiency and effectiveness. The most obvious impact will continue to be automating away low-value, repetitive work. What will surprise people will be the rapid advance and adoption of AI to suggest next best actions to take and content to use in those interactions with buyers. A typical workday for a seller will see them greeted by a recommended list of actions to take each day. Each action will be prioritized based on where the seller sits in relation to their targets, with each action accompanied by suggested content where appropriate. For instance, I might see a suggestion to respond to an email from a champion in an in-flight deal. The recommendation will include suggested text for the response as well as a resource to attach to the email. That’s a future we are actively investing in at Salesloft, which is at the heart of our soon-to-be-released Rhythm product.
Same question, but looking further out to 2030…
As AI becomes more commonly deployed across the sales profession, buyers will experience a more consistent sales experience in each buyer-seller interaction. As this becomes more common, it’s going to raise the bar on what buyers expect from a sales experience today. That will put more pressure on sales teams to deliver consistently in ways that today may seem unreasonable but will be possible with AI assistance.
One of the key ways to raise the seller performance bar will be high-impact, tailored coaching. Manager time is a constrained resource, and seller coaching augmented by AI provides a path to realizing performance improvement without manager time constraints. We should fully expect AI to help coach sellers to hit their goals based on each seller’s unique profile. We can expect AI to evaluate the seller’s entire game (activities, conversations, and deal management) to identify the highest leverage areas each individual seller should focus on to improve. Some of the coaching will be provided by AI at the point of execution, like on a call or when writing an email, with the rest provided throughout the workday as recommendations.
What are the most significant risks of deploying AI broadly across the Sales Function?
Two areas come to mind. First, AI used without clear boundaries in a sales process can lead to problems. If you employ AI and automation capabilities, it should be to allow the user to be better armed to make a decision, not make it for them. AI tools should not replace the human touch but rather augment it. There’s a lot of pseudo-science tossed up around the topic of AI, but ultimately, humans understand the nuance of relationships better than machines. One of the ways to address that concern is to deliver models that not only provide a recommendation but can provide the insights that led to it; humans will better trust the model when making decisions based on those recommendations as well as know when to ignore the recommendation.
Second, there’s a privacy component as well. Companies may create AI models that share data about a particular buyer with other companies’ sales teams without said buyer’s knowledge. The buyer may know they shared their data with one company but have no idea that multiple other customers at this company are using that same data. Creating models with this type of function puts companies and sales teams in a high-risk zone that can tread on the unethical. It isn’t clear that building models in that way may be considered legal in the future. If you plan to deploy AI in a sales org, it’s important to understand how data is collected and used.
AI Models are only as good as the underlying training data. How concerned are you about biased models recapitulating discrimination? For example, emphasizing sales skills that are gender or racially biased when evaluating sales rep performance?
It is a legitimate concern. AI products are based on probabilities, not certainties. The recommendations you receive or workflow automations that fire happen based on the probability that the given recommendation or action is right. Not the certainty that it is right. In a good product, the model is correct more often than a human would be when faced with the same decisions. At times, this is because the model can evaluate a larger set of factors, and in some cases, it is simply that machines can apply rulesets at a higher level of consistency than humans.
One of the key determinants of the AI model’s value is the dataset upon which it was trained. If the dataset does not properly represent the real world, the model will produce results that are either biased or provide poor recommendations. We’ve already seen several examples of that with image editing software that didn’t include black-skinned people in the training dataset. This led to either poor outcomes or worse dehumanizing results when the AI product was used in the real world. If you plan to deploy AI in your business, you should ask the provider what precautions they take to prevent bias in their models. We are very intentional about removing factors that could lead to bias in our training datasets. Still, it isn’t something I see most technology companies paying attention to in the revenue tech space.
How do you curb racial and gender bias when performing sentiment analysis?
We take great care at Salesloft to remove things that would lead to discriminatory factors. For example, for our Email Sentiment model, one of the ways we prevent bias is by removing all mentions of people’s names within the email because that could provide clues to their gender, race, or ethnicity. We do that kind of preprocessing with any data we use in an AI model before we build our models.
One of our assets is our scale. We’re fortunate that we operate globally and are the only provider in our space with offices in the Americas, Europe, and APAC. As a result, we work with organizations of all sizes globally, including many of the world’s largest companies. That means when we build models, we have one of the largest datasets in the world for sales execution. This enables us to train models based on datasets with both breadth and depth. When we build a model, it is easier to train it in a way that fairly represents reality and includes safeguards to avoid racial or gender bias.
AI will increasingly be deployed for recommending coaching and mediating the coaching. What concerns do you have about replicating bias when coaching?
As with any AI product making a recommendation, the potential to make a recommendation with bias is a concern that needs to be addressed when building models.
We take our responsibility to avoid bias in any product we release very seriously. The revenue technology industry as a whole hasn’t demonstrated a similar commitment to avoid harmful bias as of yet. I don’t hear other companies talking about proactive steps to avoid it, but I think that will change. We’re monitoring potential governmental action in both the US and EU that will require companies to raise their standard in this area. It is only a matter of time before laws are passed that require companies to prevent unlawful bias in their AI products.
Sales activities are becoming increasingly digitized, a boon for revenue intelligence, training, and next best actions. What guardrails do we need to put in place to ensure that employee monitoring does not become overly intrusive and invade privacy?
Let’s start by recognizing it is reasonable for an employer to have insight into what work is getting done and how it’s getting done. On the other hand, getting a minute-by-minute record of how each seller spends their day is unreasonable, as is dictating every action the seller takes from morning until nightfall.
We have to start with the right first principles. I think we can all agree that humans have inherent worth and dignity. They don’t lose that when they go to work. The challenge is that we have some companies in the technology industry that forget that fact when developing solutions. When you forget that fact, I believe that you actually harm the customer that you’re trying to serve. That harm happens in two ways.
First, you lose the opportunity to realize the true potential of AI, which is to serve as a partner that enables humans to do what they do best…which is to engage with and relate to other humans. AI should not be used to make final decisions for humans or to dictate how they spend every minute of their day. Good AI solutions should be thought partners and assistants to humans. It’s Jarvis to Tony Stark’s Iron Man.
The second way overly intrusive technology harms companies that employ it is via employee turnover. It’s no secret that industries that offer low autonomy to employees suffer from high turnover. Most humans fundamentally desire a base level of autonomy; if that’s threatened, they leave whenever a good option opens up.
In short, if the seller is working for the technology instead of the inverse relationship, we’re on the wrong path.
In 2018, Salesforce CEO Marc Benioff argued that the best idea is no longer the most important value in technology. Instead, trust must be the top value at tech companies. How does trust play into ethical applications and AI?
We get to build the future we want to realize. We can either build a future that perpetuates the things we don’t like about today’s world, or we can build a future that elevates human potential. AI can be used to take us in either direction. That means what we choose to build with AI and how we build it should be a very value-driven decision.
We can absolutely build highly effective AI-powered solutions that elevate the people who use them and deliver tremendous business value. The people that believe otherwise simply lack the imagination and skill to do it.
What I love about our team at Salesloft is that we exist to elevate the ability of the people we serve and to enable them to be more honestly respected by the buyers they serve. In sales and life, the way you win matters. It matters to the people you serve on your revenue team, and it matters to your customers.
An emerging category of AI called Generative AI constructs content (e.g., images, presentations, emails, videos). It was just named a disruptive sales technology by Gartner. They stated that “By 2025, 30% of outbound messages from large organizations will be synthetically generated.” What risks do you see from this technology?
There are two immediate risks that come to mind. First, the messages need to be reviewed by a human before they are sent. The technology has made extraordinary leaps forward. I’ve spent a fair amount of time playing around with some of the tools released by OpenAI and others. The output is impressive and also, at times, very wrong. This goes back to the fact that the output is based on a probability that the answer provided is correct. You can get a very professional, persuasive email, or you can get something that approximates a professional email but won’t land well with your intended customer.
Second, it has the potential to make every outbound message sound the same. Generative AI doesn’t replace the need for human skill. It changes the areas of focus for that skill. Specifically, the opportunity for humans is to use Generative AI to help generate a higher volume and variety of ideas and then to edit and refine the output. The returns available to creativity are always high, but they become even higher when everyone is doing the exact same thing in the same way.
Having said that, I see tremendous potential in the technology and think if used properly it will be very valuable to revenue professionals.
SalesLoft CEO Kyle Porter has long emphasized authenticity and personalization in sales conversations. Do you see Generative AI potentially undermining trust?
Kyle is absolutely right. At the end of the day, a sale happens when a seller connects with a buyer to help them solve a problem. You can’t do that without authentic connection and trust. Generative AI should not replace that human connection, and I don’t think buyers want it to replace human connection. A close friend of mine was a sales leader at a now-public PLG-driven SaaS company. They added sales reluctantly. When they did, the company learned that buyers both bought more from them and were happier customers. That company now wishes it had added sales much earlier. How we interact with one another can evolve as technology evolves, but it doesn’t change the fact that humans are wired to connect with each other. I think emerging tools like Generative AI will help us be more productive, but they won’t replace the need for authentic human connection and trust.
People.AI announced a partnership with Zoom Video Communications to deliver its sales engagement intelligence alongside Zoom’s conversational intelligence within Zoom IQ for Sales. People.AI buyer role and engagement insights will be combined with Zoom’s conversational sales intelligence. The joint solution also supports cross-channel engagement data, post-call summaries, and contact creation and enrichment.
The combined solution will provide “greater visibility into buyer engagements, enabling go-to-market teams to access previously buried insights,” said the firms. “Sellers will have the ability to engage the right people in the right accounts, resulting in pipeline predictability and revenue.”
Revenue teams will enjoy greater pipeline visibility, helping de-risk deals and drive revenue growth. During calls, a side panel will provide an “unparalleled understanding of ‘who is who’ within accounts and opportunities, empowering your sales teams to strategically plot next steps with the right people and personas to grow pipeline, drive larger deals, shorten sales cycles, and improve win rate.”
“Zoom has been a customer of ours since 2017 and a business we’ve always admired,” said Thomas Wyatt, Chief Product and Strategy Officer at People.ai. “Our joint customers will soon be able to leverage Zoom’s world-class conversation intelligence solution enriched by buyer and relationship intelligence that only People.ai can provide.”
During Zoom Calls, People.AI displays Stakeholder Insights that include contact information, engagement levels, and connection overviews.
Zoom IQ for Sales was launched in April and provides a host of standard conversational sales capabilities, including sentiment analysis, engagement scores, talk-listen ratios, the longest monologue, filler word frequency, a snippets library, and competitor and feature mentions. Furthermore, it includes a few differentiators:
Engaging Questions – Analyzes questions posed to determine the frequency with which customers respond to queries.
Next Steps – Assesses whether clear next steps are outlined during the meeting.
Patience – Determines whether reps wait for a response after asking a question.
Post-deal analytics include which topics arose most frequently, time spent in each stage, and which negotiators made the final purchasing decision. General Deal analytics include the number of conversations per deal and the duration of conversations per deal.
Zoom IQ for Sales is available for Zoom and Zoom Phone. It is “tightly integrated” with Salesforce, Google Calendar, Office 365, and Exchange. Zoom IQ for Sales is priced at $79 per month per seat.
Microsoft announced Viva Sales, “a new seller experience application that brings together any customer relationship management technology (CRM), Microsoft 365, and Teams to provide a more streamlined and AI-powered selling experience.” The new solution is designed for the hybrid work environment where reps leverage video conferences, chats, emails, and documents to close deals. Viva Sales will also support Salesforce at launch.
Viva Sales “represents a new way of working by breaking down silos of data and breaking down silos of experience,” explained Microsoft Corporate VP for Business Applications Emily He. Sales reps “really want a more simplified experience. So, Viva Sales enables a seller to use the tools they already love and use every day, including your email system like Outlook, Word documents, PowerPoint presentations, as well as Teams,” she said.
Unfortunately, reps manage these disparate communications channels and their CRM to organize administrative tasks, collaborate on sales, and attend virtual sales meetings. “Yet, all sellers really want is to spend more time with their customers,” stated Microsoft Chief Commercial Officer Judson Althoff.
Continued Althoff, “What if everything a salesperson needed to do their job was brought together in one place – where they already spend most of their day – in calls, meetings, and chats? What if their customer records, data, and tasks were intelligently organized and accessible in the tools they use every day? What if the collaboration environment sellers use to talk to customers automatically provides the next best action and sentiment analysis?”
Viva Sales is a “new modern way of selling” that operates as a “smart CRM companion” that simplifies the seller’s workflows and enriches the CRM. Viva Sales captures AI-driven insights from Outlook, Teams, and Microsoft Office and feeds this information to the CRM.
“Viva Sales empowers sellers to be more connected with their customers, resulting in more personalized customer engagements and closed deals faster,” stated Althoff. “This happens through a simple customer tagging feature, which automates the data capture, saves the seller time, and provides their organization with a more complete picture of deal and customer status. With AI embedded throughout, Viva Sales is like a sales coach to move deals along with recommendations and reminders. This intelligence layer provides sellers the information they need to help them be more productive.”
Viva was launched last year as an employee portal, but Sales is the first functionally-specific edition of the service. Viva Sales will be in public preview in July and generally available this fall. Microsoft Dynamics Sales is inclusive of Viva Sales and “addresses both sellers’ and sales leaders’ needs by automatically enriching Dynamics 365 Sales with customer engagement data captured in Office 365 and Teams.”
Once an email is tagged to an account, Viva Sales presents a sidebar with CRM intelligence. Customer interactions are then logged to the CRM.
Sales reps tag customers or prospects in a Microsoft application. This “tag to capture” functionality alerts Viva to begin capturing account intelligence and offering insights to the sales rep. Viva Sales employs Microsoft’s recently announced Context IQ for capturing relevant content across Microsoft apps and services. This data can then be synced with any CRM.
“What we are focused on is removing the drudgery of manually entering the data into a CRM and then providing the AI capabilities for the sellers,” explained Product Marketing Senior Director Neha Bajwa. “There’s a virtual personal assistant that is sitting and helping them out doing all the busywork that we would normally have to do.”
The objective is to solve the problem of manual data entry without destroying the CRM. Viva runs alongside the CRM, capturing intelligence from other enterprise sales apps commonly deployed across sales teams. The data capture and CRM syncing improve rep productivity while the AI suggestions improve sales effectiveness through better recommendations, reminders, and Next Best actions.
“As you work with a customer, you can not only see your own interactions, [but] you can also see across your company and find all the people that are interacting with your client as well,” said Microsoft VP for Modern Work Jared Spataro. “We’re trying to apply AI not only to remove the boring stuff, but also to provide real value add so that you can cope with the volume and the expectations associated with you doing your job.”
The service recommends next steps, displays complete interaction histories, and pushes reminders to reps. It is also connected to LinkedIn, providing the names of colleagues with strong connections to a contact or account, allowing sales reps to conduct research before a Teams chat.
Viva Sales recommends colleagues with pre-existing relationships for pre-meeting briefings via Teams Chat.
During a Teams call, reps can view the relevant customer information in a sidebar and access meeting prep notes. After the call is recorded and transcribed, Viva Sales summarizes the call and captures action items. Conversation KPIs and talk tracks are also generated.
Another feature is the generation of customer lists with recent activity, sentiment graphs, and engagement within Excel.
Customer lists within Excel are enriched by Viva Sales. A sidebar provides contact-specific insights, including colleague connections and meeting summaries.
“The future of selling isn’t a new system. It’s bringing the information sellers need at the right time, the right context, into the tools they know, so their work experience can be streamlined,” said Althoff. “Empowering sellers to spend more time with their customers has been our goal — and we’ve done that by reimagining the selling experience with Viva Sales.”
One of the core issues at the heart of CRM implementations is the reliance on manual data entry, argued Paul Greenberg, Managing Principal at The 56 Group. What is necessary is ongoing automation to remove this busy work.
“Sellers rely on digital collaboration and productivity tools to connect with customers and close deals, but a lot of the insights they uncover with these tools don’t make it into the CRM,” Greenberg. “Microsoft is taking on this challenge by offering a solution that complements the CRM. Viva Sales automates the busy work, captures critical information about the customer, and helps sellers get the job done.”
“Zoom IQ for Sales analyzes customer interactions to surface key insights, actions, and content from sales meetings. Sales leaders can also use this data to help make better-informed management decisions regarding their sales teams,” blogged UCaaS Product Marketing Manager Theresa Larkin. “With actionable insights based on proven sales strategies and a wealth of data, organizations can streamline the new sales rep onboarding process, create a modern sales methodology, and further develop their sales teams.”
Zoom IQ for Sales conversational analytics
Zoom describes Zoom IQ for Sales as its “First Step in Conversational Intelligence.” The service is “tightly integrated” with Salesforce, Google Calendar, Office 365, and Exchange. Insights include
Engaging Questions – Analyzes questions posed to determine the frequency with which customers respond to queries.
Longest Spiel – Identifies the longest monologue to help reps hone their pitches and avoid monologues.
Next Steps – Assesses whether clear next steps are outlined during the meeting.
Patience – Determines whether reps wait for a response after asking a question.
Talk-Listen Ratios – Analyzes whether there is a balance between lead speaker talk time and time granted to others.
Competitor and Feature Mentions – Tags competitors and product features so reps, competitive analysts, and product teams can drill into prospect concerns, competitive statements, and potential gaps in the product.
Post-deal analytics include which topics arose most frequently, time spent in each stage, and which negotiators made the final purchasing decision. General Deal analytics include the number of conversations per deal and the duration of conversations per deal.
Zoom IQ supports a video snippets library of best practices exemplars. Snippets can be used for initial training or for reviewing how to handle specific objections, present the value of various products, or position across target verticals.
Zoom Sales IQ Playlists
“Zoom has made strategic investments in homegrown speech recognition technologies and recruited a world-class team to produce high-fidelity transcription services that are a backbone for products like Zoom IQ…We’re developing domain-specific NLU (natural language understanding) using few-shot models to build features that will be more reliable and valuable to our users,” said Josh Dulberger, Zoom’s head of product, data, and AI. “Sales teams…want to focus on the customer, and managing the engagement rather than taking notes, but also so they can review their calls to pick up nuances, easily identify next steps, or solicit some guidance from a colleague. Managers and sales leaders can’t sit in on every call but want to understand the selling climate, when to coach, and which reps are finding the right message.”
Zoom IQ for Sales places Zoom in competition with many of its partners, including Salesloft, Outreach, Chorus, and Gong.
TechCrunch Senior Report Kyle Wiggers cautioned buyers about Zoom’s AI capabilities: “The jury’s out on the accuracy of Zoom’s algorithms, particularly given the company’s history of deploying flawed AI. Sentiment analysis algorithms are especially prone to gender and race bias, and not every salesperson will necessarily agree with how Zoom measures engagement.”
“Zoom is almost certainly feeling the pressure from investors to establish new lines of revenue,” continued Wiggers. “While the company’s earnings soared during the pandemic, guidance is down as customers begin to shift to hybrid and in-office work arrangements less reliant on videoconferencing.”
Zoom IQ for Sales is priced at $79 per month per seat.
“Half a million businesses choose Zoom and rely on it for internal and external conversations,” said Dulberger. “The Zoom platform already has a strong foundation in this area with features such as transcription, recordings, and highlights. This also gives us an opportunity to expand this type of functionality across the Zoom platform such as Zoom Contact Center and within our meetings and events solutions to help presenters pace their speech, take notes, capture action items or employ specific tactics.”
Zoom Events, Zoom’s platform for virtual and hybrid shows, is adding a backstage feature that lets panelists, speakers, and production crews meet before, during, and after events. During the session, support staff can view the webinar feed, chat with each other, answer attendees’ questions, and practice their presentations. Zoom Events Backstage should be available by the end of April.
Other new Events features include branded wallpaper that displays behind tiles and webinar reactions.
The Outreach Deal Summary provides an opportunity overview, recent activity, and access to Kaia, Commit, and Success Plans.
Sales Engagement Platform vendor Outreach will be rolling out AI-Guided Deal Intelligence in 2022. The new Deal Insights functionality provides a consolidated opportunity view that includes a deal overview, deal health, risks, and next best action recommendations from a single pane of glass.
“Deal Intelligence doesn’t just warn you a deal is off track but will actually guide you to help understand what you can do now, in the moment, to change the outcome,” explained Senior Communications Manager Amanda Woolley to GZ Consulting. “Deal Intelligence is going to reach across the Outreach platform and gather signals from all facets of the platform and throughout the customer journey and move from risk identification into action.”
Many of the components of Deal Intelligence such as Sentiment Analysis, Success Plans, Kaia, Commit, and engagement monitoring already exist in the Outreach platform, with the new Deal Intelligence tying together data and insights from the various modules and summarizing them with deal health and next best action recommendations.
“Built on the foundation of our deep machine learning tools like Kaia, Intent, title classification, and more, Deal Intelligence will help remove some of the “best guesses” we revenue leaders have been doing,” explained Outreach CRO Anna Baird. “Deal Intelligence will be gathering signals and let us know – not only when we have a risk – but what we can do to change the outcome! It’s not just a warning light, but a full explanation of how to correct the issue. Deal Intelligence will bring true transparency to opportunity management and help us get to that predictable revenue goal we all want.”
Deal intelligence is gathered across the deal lifecycle and ongoing customer interactions, including sequences, email sentiment, calendaring, Outreach Kaia (conversational intelligence and real-time recommendations), Success Plans (digital salesrooms), and Outreach Commit (pipeline health and forecasting).
“The current ML model looks at the multiple factors and compares them across benchmarks we have collected to derive the [Health Insights] score,” explained Woolley. “Some of the key top-level factors included Decision-maker engagement, activity across email and calls, meeting analysis as well as interaction within Success Plan. For every deal, the ML model determines which factors are positive (‘green flag’) or negative polarity (‘red flag’).”
Both red and green flags are displayed in Deal Intelligence. The Deal Intelligence service summarizes relevant signals, but “given the number of signals captured, it is very hard for a sales rep to drill through every deal.” Outreach’s goal is to “surface all the relevant information for the sales rep in a unified view with the ability to drill deeper as well as take action from within Outreach.”
“Sales reps only succeed when they take the right actions to close deals, yet for far too long they have lacked true visibility into the health of their deals and are forced to turn to intuition and guesswork to select the next best actions to take. Sales leaders and reps have to contend with disparate, dated sales technologies as they strive for an accurate understanding of their deals, pipeline, and forecast. CRM solutions provide a way to store data but rely on extensive tedious manual data entry from sales reps, often resulting in a “garbage-in garbage-out” situation that does not help reps or managers make confident decisions. Point solutions like conversation intelligence offer a way to record conversations and glean insights hours or days later, but at best, they can tell what the reps’ next actions in other systems should be. All are failing to deliver deal observability. And none of them give real-time deal intelligence to sales reps and seamlessly automate the next actions all in one continuous experience. Until now, that is.”
Outreach CMO Melton Littlepage
Part II continues tomorrow with a discussion of Outreach deal health analytics across the deal lifecycle.
Conversational Sales and Marketing vendor Qualified announced select availability for its new Signals intent product. Qualified Signals delivers sales intelligence gleaned from company websites, helping them identify in-market accounts and prioritize their outreach.
Qualified Signals is an “AI product that combines website engagement with Salesforce data to surface the buying intent of a B2B company’s target accounts; helping sales reps focus on exactly the right accounts to generate more pipeline and revenue,” blogged Qualified CRO Robert Zimmerman.
When ABM was proposed as the successor to lead-generation marketing, it focused on defining the ICP and targeting accordingly. While the ICP concept is still important, it fails to recognize that at any one moment, most ICP accounts are not in-market. Thus, a further refinement was in order, deploying intent (e.g., visitor intelligence, chatbots, third-party B2B website activity) and engagement data (e.g., email responses, meeting attendance, sentiment) to prioritize accounts so that sales reps focus on the accounts that are in market and marketing continues to nurture ICP accounts with low-level intent signals.
“Sales reps need a simple way to identify the accounts with high purchase intent so they can maximize pipeline more efficiently,” argued Zimmerman. “Meanwhile, target accounts are poking around the website and signaling buying intent, but sales reps have no idea. This is a missed opportunity because website engagement is a critical predictor of purchase intent. It demonstrates patterns of website activity that indicate whether an account is sales-ready.”
Unfortunately, website activity is a “blind spot for salespeople” that leaves them “in the dark as to where to focus their attention, how to engage target accounts, and how deals are progressing.”
Qualified Signals employs an AI-predictive model that collects “hundreds of thousands of website data points to determine which accounts are in-market to buy and sales-ready.” Models include website activity such as mouse movement, clicks, scroll depth, page views, active time on site, chatbot engagement, live chat, voice calls, meetings booked, recency and frequency of visits, and visitor count.
“In a booming sales tech market, there are countless sales intelligence tools out there, but they often overlook the most important sales and marketing asset—the corporate website,” said Qualified CEO Kraig Swensrud. “Signals arms sellers with an entirely new type of buying intent data, so revenue teams know exactly which accounts to pursue to crush their quota.”
The Qualified Signals Account Trend Report analyzes buyer activity on the company website across a rep’s territory, helping her prioritize activity and identify accounts where activity is cooling.
Signals are displayed to sales reps in the Salesforce Account record and convert complex buyer behavior into straightforward trends such as cooling, neutral, heating, and surging. Trend data “can also be customized using unique Salesforce Account data to home in on the accounts that matter most, like ABM tier, account owner, region, or industry.”
Signals optionally pushes custom Account intent fields to Salesforce, which can then be built into custom reports and dashboards.
Qualified also displays Signals Account 360, a dynamic graph that visualizes purchase intent fluctuations over time for individual accounts. Signals are expressed as a current Heat Index temperature, dynamic trend, and detailed account activity view that replays account engagement at the contact level. The account timeline “offers a detailed, highly visual, timestamped overview of notable website events that occurred throughout the buying process,” blogged Zimmerman.
The Account 360 view combines heat index trend data alongside visitor intelligence.
Additionally, Signals supports mobile, email, and Slack alerts when an account hits client specified thresholds on the Qualified Heat Index. Alerts may be sent in real-time or included in a daily or weekly email digest.
“Qualified Signals amplifies Qualified X, bringing purchase intent data to the visitor level within your conversational sales and marketing application,” stated the firm. “When a sales rep prospects into a target account, they’re instantly notified when that account arrives on the site. Plus, they have all intent data at the ready. They can instantly meet with the prospect using a full stack of meeting tools, including chat, voice, and screen-sharing.”
Due to the complexity of visitor intelligence and similar data, intent signals have mostly been fed into marketing platforms and not converted into actionable semaphores; however, sales intelligence vendors have begun enabling these signals.
“The website is no longer just for marketers; it’s now a window into your biggest sales opportunities. Sellers have their standard indicators that an account is interested, and a deal is moving forward; but in between the standard touchpoints, prospects are poking around your website, reading a customer story, or engaging via live chat. Sellers have had limited insight into how target accounts are exploring this property, but the website is an amazing predictor of intent. Now, Qualified Signals will surface this invaluable insight for revenue teams.”
Qualified CEO Kraig Swensrud
Qualified Signals will GA in early 2022.
Qualified closed on a $51 million Series B round in May that Salesforce Ventures led. The firm describes itself as “the only conversational sales and marketing platform purpose-built for Salesforce Sales Cloud.”
Qualified Insights delivered via Slack and mobile devices.
Outreach Commit supports forecasting, scenario planning, and deal risk analysis.
Sales Engagement Platform Outreach expanded its value proposition with the acquisition of Revenue Intelligence service Canopy. Outreach immediately began integrating the service into its platform, with GA expected in H1 2022. The new Outreach Commit service “significantly expands” Outreach’s revenue intelligence capabilities, “giving revenue leaders the sales analytics and forecasting capabilities they need in today’s sales environment.”
“In the past 18 unpredictable and transformative months, we have seen the rise of a new cohort of leaders we are calling Revenue Innovators who have thrived by embracing the digital disruption of sales,” said Outreach CEO Manny Medina. “These are leaders who had to adapt and evolve their mindset to embrace automation and machine learning as the keys to driving predictable, efficient growth – consistently and despite the uncertainty in the market. They need tools that combine engagement with intelligence and marry together the art and the science of sales. The evolution of the Outreach platform does exactly that.”
Outreach provides revenue innovators with “predictable, efficient growth” based upon AI guidance for more effective engagement, improved forecasting, and next best actions. The objective is to reduce the “Sales Execution Gap” between revenue potential and actual performance based on instinct and limited data; instead, data and AI will narrow the gap.
“The Sales Execution Gap manifests itself in several ways across the business — decisions based on gut instincts, slow rep ramp times, competing priorities, random achievement, missed opportunities with little understanding as to why,” explained Medina. “And yes, lost revenue, but also a growing disconnect between what high-performing reps want and what employers can deliver.”
“Once a seller has experienced the power of an Engagement and Intelligence platform, they won’t want to go back to inefficient, broken workflows — and they’re making career decisions because of it.”
Outreach CEO Manny Medina
Unfortunately, CRMs were “not designed for sellers.” They are systems of record that store information but lack engagement and insights. Firms that want reps to “live in the CRM” will drive away their best sales reps and candidates who “demand AI-driven insights and workflow automation to guide their actions in real-time.” As more sellers become “digital natives,” this performance gap will widen.
Top-performing reps and managers that have enjoyed modern SalesTech tools will be reluctant to work without digital tools. They expect their sales toolbox to include AI-generated intelligence, including email sentiment, live meeting guidance, real-time call analysis, and automated deal review and scoring. They are also looking for sales engagement with templated sequences (cadences), multi-channel outreach, task prioritization, and recommended actions. Finally, they are looking for improved forecasting, risk alerts, engagement data, and deal facilitation.
With Commit, Outreach has added forecasting and expanded risk analytics to its toolkit.
Outreach sees a bifurcation between traditional sales organizations and revenue innovators that have adopted digital communications and AI for outreach, prioritization, coaching, forecasting, and analytics.
“Revenue innovators are embracing automation and AI in real-time to provide guidance to reps mid-cycle, guide more effective engagement with customers, and entirely rethink how they forecast because they have the signals that can proactively identify risk in their pipeline and deals,” stated the firm.
Continue to Part II which discusses Outreach Commit and product enhancements announced at the Outreach Unleash virtual meeting.
